A Data-Driven InSAR Failure-Risk Index for Early Warning of Mining Infrastructure Instability: The Çöpler Case Study, İliç, Türkiye.
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| Title: | A Data-Driven InSAR Failure-Risk Index for Early Warning of Mining Infrastructure Instability: The Çöpler Case Study, İliç, Türkiye. |
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| Authors: | Cavur, Mahmut1 (AUTHOR) |
| Source: | Remote Sensing. Aug2026, Vol. 18 Issue 15, p2624. 30p. |
| Subjects: | Deformations (Mechanics), Radar interferometry, Mines & mineral resources, Strip mining, Risk managers |
| Geographic Terms: | Türkiye, Erzincan (Türkiye) |
| Abstract: | Highlights: What are the main findings? A novel InSAR-based Failure-Risk Index (FRI) integrates displacement, velocity, and especially deformation acceleration into a single standardized early-warning metric for mining infrastructure. Deformation acceleration exhibited a statistically significant regime change beginning in 2020—approximately four years prior to the February 2024 Çöpler Mine collapse—providing a substantially earlier warning than velocity-based methods. What is the implication of the main finding? Acceleration-based monitoring enables statistically significant change-point detection, transforming Interferometric Synthetic Aperture Radar (InSAR) from a descriptive monitoring tool into a proactive early warning system for open-pit mines and tailing dams. The transferable 0–2 FRI classification framework supports risk-based decision-making, emergency protocol activation, and improved operational safety in large scale mining environments. Failures at large-scale open-pit mines and tailing dams pose critical risks to human life, environmental systems, and economic sustainability. Although Interferometric Synthetic Aperture Radar (InSAR) has proven effective in detecting long-term surface deformation, a scientifically robust early-warning framework has not yet been established because standardized quantitative thresholds that are capable of distinguishing benign consolidation settlement from instability-driven deformation remain unavailable.InSAR has proven effective for detecting long-term surface deformation. However, a scientific early-warning framework has not yet been proposed or developed due to the absence of standardized quantitative thresholds that distinguish benign consolidation settlement from instability-driven deformation. This research proposes a novel InSAR-based Failure-Risk Index (FRI) that integrates displacement, velocity, and, most importantly, deformation acceleration into a single, normalized metric as an early warning system for mining infrastructure instability. The framework that we propose (i) emphasizes acceleration as a leading indicator of change in mechanical regime, (ii) incorporates a statistically guided separation of long-term consolidation settlement from anomalous deformation based on baseline variability, (iii) applies a statistical standardization and change-point detection system. The methodology is validated through a retrospective analysis of the heap leach failure—that occurred in Çöpler Gold Mine in Erzincan, Türkiye, on 13 February 2024—by using a set of Sentinel-1 time-series images collected between 2014 and 2024. The results prove that while displacement and velocity remained within ranges typically interpreted as stable, deformation acceleration exhibited a statistically significant increase that began around 2020, exceeded baseline variability by approximately two orders of magnitude, which is approximately four years before the collapse, and marked the onset of tertiary creep and progressive instability. The proposed FRI framework successfully captures this transition and provides a transferable, meaningful early-warning framework to support proactive risk management and improve the safety of mining infrastructure. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? A novel InSAR-based Failure-Risk Index (FRI) integrates displacement, velocity, and especially deformation acceleration into a single standardized early-warning metric for mining infrastructure. Deformation acceleration exhibited a statistically significant regime change beginning in 2020—approximately four years prior to the February 2024 Çöpler Mine collapse—providing a substantially earlier warning than velocity-based methods. What is the implication of the main finding? Acceleration-based monitoring enables statistically significant change-point detection, transforming Interferometric Synthetic Aperture Radar (InSAR) from a descriptive monitoring tool into a proactive early warning system for open-pit mines and tailing dams. The transferable 0–2 FRI classification framework supports risk-based decision-making, emergency protocol activation, and improved operational safety in large scale mining environments. Failures at large-scale open-pit mines and tailing dams pose critical risks to human life, environmental systems, and economic sustainability. Although Interferometric Synthetic Aperture Radar (InSAR) has proven effective in detecting long-term surface deformation, a scientifically robust early-warning framework has not yet been established because standardized quantitative thresholds that are capable of distinguishing benign consolidation settlement from instability-driven deformation remain unavailable.InSAR has proven effective for detecting long-term surface deformation. However, a scientific early-warning framework has not yet been proposed or developed due to the absence of standardized quantitative thresholds that distinguish benign consolidation settlement from instability-driven deformation. This research proposes a novel InSAR-based Failure-Risk Index (FRI) that integrates displacement, velocity, and, most importantly, deformation acceleration into a single, normalized metric as an early warning system for mining infrastructure instability. The framework that we propose (i) emphasizes acceleration as a leading indicator of change in mechanical regime, (ii) incorporates a statistically guided separation of long-term consolidation settlement from anomalous deformation based on baseline variability, (iii) applies a statistical standardization and change-point detection system. The methodology is validated through a retrospective analysis of the heap leach failure—that occurred in Çöpler Gold Mine in Erzincan, Türkiye, on 13 February 2024—by using a set of Sentinel-1 time-series images collected between 2014 and 2024. The results prove that while displacement and velocity remained within ranges typically interpreted as stable, deformation acceleration exhibited a statistically significant increase that began around 2020, exceeded baseline variability by approximately two orders of magnitude, which is approximately four years before the collapse, and marked the onset of tertiary creep and progressive instability. The proposed FRI framework successfully captures this transition and provides a transferable, meaningful early-warning framework to support proactive risk management and improve the safety of mining infrastructure. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18152624 |
